Current developments in AI to improve patient care are being driven by research happening primarily at institutions with extensive informatics and data science resources — and primarily using single-institution patient data. Yet repeated studies have shown that these deep learning models do not generalize well across institutional differences, such as patient demographics, disease prevalence, scanners, and acquisition settings[2] [3]. Although AI algorithms are more effective when trained on a wide and diverse array of clinical data, sharing data outside an institution is difficult due to patient privacy concerns.  With ACR AI-LAB, the intention is to share AI models between institutions leaving patient information to remain on-site at the originating institution.  Emory is one of the 7 sites participating to pilot the infrastructure required to create such a federated environment.

For the first part of this pilot, we are testing breast density algorithm brittleness across 10 Emory sites performing screening mammograms. This project has subprojects